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domino-modeling-assistant

Execute Domino jobs and manage project files via MCP integration.

Updated Apr 11, 2026
Search Tags:#mlops#mcp#mlflow#job-orchestration#domino#modeling-assistant
One-click install
npx skills add https://github.com/ToXMon/tolu --skill domino-modeling-assistant
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: domino-modeling-assistant
Source: https://github.com/ToXMon/tolu/tree/main/agent-zero-backup/workdir/memory-palace/skills/domino/domino-modeling-assistant
Command: npx skills add https://github.com/ToXMon/tolu --skill domino-modeling-assistant

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the friction of running and managing model development workflows on Domino by enabling AI coding assistants to create, run, and monitor Domino jobs, handle project files, and ensure reproducibility without manual terminal steps.

Core Features & Use Cases

  • MCP integration & environment detection: Automatically detect Domino workspace vs laptop and configure authentication, project owner, and project name.
  • Job orchestration and results retrieval: Create and run Domino jobs, monitor status, fetch stdout and artifacts, and open experiment links when available.
  • DFS vs Git file handling and experiment tracking: Sync files to DFS or require git commits before job execution, and instrument training runs with MLflow for reproducible experiments.
  • Use Case: Ask the assistant to run a data analysis script in your Domino project, return the summary output, save artifacts to the project, and log the run to MLflow.

Quick Start

Run the test_domino.py script as a Domino job and show me the stdout output and any saved artifacts.

Frequently Asked Questions about domino-modeling-assistant

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run Domino jobs using an AI coding assistant?▼

You can run Domino jobs via an AI assistant by using an MCP integration that creates, executes, and monitors job status while fetching stdout and artifacts automatically without manual terminal steps.

Can I track MLflow experiments when running model training on Domino?▼

Yes, you can track MLflow experiments on Domino by instrumenting training runs directly through the assistant, which logs models for reproducibility and opens experiment links when available.

Do I need DOMINO_API_KEY and DOMINO_HOST to manage projects from my local laptop?▼

Yes, you need DOMINO_API_KEY and DOMINO_HOST to manage Domino projects from a local laptop, because external use requires MCP server connectivity to authenticate with Domino APIs.

How does file handling work for Domino Data Lab projects using DFS versus Git?▼

File handling for Domino Data Lab projects either syncs files to DFS or requires Git commits before job execution, ensuring project files and artifacts are managed correctly before running scripts.

What is the best way to automate dataset exploration on Domino without manual terminal steps?▼

The best way to automate dataset exploration on Domino is using an AI assistant with MCP integration to detect your workspace environment, configure authentication, and orchestrate analysis jobs automatically.

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